DNA extraction from primary liquid blood cultures for bloodstream infection diagnosis using whole genome sequencing.

PURPOSE: Speed of bloodstream infection diagnosis is vital to reduce morbidity and mortality. Whole genome sequencing (WGS) performed directly from liquid blood culture could provide single-assay species and antibiotic susceptibility prediction; however, high inhibitor and human cell/DNA concentrations limit pathogen recovery. We develop a method for the preparation of bacterial DNA for WGS-based diagnostics direct from liquid blood culture. METHODOLOGY: We evaluate three commercial DNA extraction kits: BiOstic Bacteraemia, Amplex Hyplex and MolYsis Plus. Differential centrifugation, filtration, selective lysis and solid-phase reversible immobilization bead clean-up are tested to improve human cells/DNA and inhibitor removal. Using WGS (Illumina/MinION), we assess human DNA removal, pathogen recovery, and predict species and antibiotic susceptibility inpositive blood cultures of 44 Gram-negative and 54 Staphylococcus species.Results/Key findings. BiOstic kit extractions yield the greatest mean DNA concentration, 94-301 ng µl-1, versus 0-2.5 ng µl-1 using Amplex and MolYsis kits. However, we note higher levels of inhibition (260/280 ratio 0.9-2.1) and human DNA (0.0-4.4×106 copies) in BiOstic extracts. Differential centrifugation (2000 g, 1 min) prior to BiOstic extraction reduces human DNA by 63-89 % with selective lysis minimizing by a further 62 %. Post-extraction bead clean-up lowers inhibition. Overall, 67 % of sequenced samples (Illumina MiSeq) contain <10 % human DNA, with >93 % concordance between WGS-based species and susceptibility predictions and clinical diagnosis. If >60 % of sequencing reads are human (7/98 samples) susceptibility prediction becomes compromised. Novel MinION-based WGS (n=9) currently gives rapid species identification but not susceptibility prediction. CONCLUSION: Our method for DNA preparation allows WGS-based diagnosis direct from blood culture bottles, providing species and antibiotic susceptibility prediction in a single assay.

Nested Russian Doll-Like Genetic Mobility Drives Rapid Dissemination of the Carbapenem Resistance Gene blaKPC.

The recent widespread emergence of carbapenem resistance in Enterobacteriaceae is a major public health concern, as carbapenems are a therapy of last resort against this family of common bacterial pathogens. Resistance genes can mobilize via various mechanisms, including conjugation and transposition; however, the importance of this mobility in short-term evolution, such as within nosocomial outbreaks, is unknown. Using a combination of short- and long-read whole-genome sequencing of 281 blaKPC-positive Enterobacteriaceae isolates from a single hospital over 5 years, we demonstrate rapid dissemination of this carbapenem resistance gene to multiple species, strains, and plasmids. Mobility of blaKPC occurs at multiple nested genetic levels, with transmission of blaKPC strains between individuals, frequent transfer of blaKPC plasmids between strains/species, and frequent transposition of blaKPC transposon Tn4401 between plasmids. We also identify a common insertion site for Tn4401 within various Tn2-like elements, suggesting that homologous recombination between Tn2-like elements has enhanced the spread of Tn4401 between different plasmid vectors. Furthermore, while short-read sequencing has known limitations for plasmid assembly, various studies have attempted to overcome this by the use of reference-based methods. We also demonstrate that, as a consequence of the genetic mobility observed in this study, plasmid structures can be extremely dynamic, and therefore these reference-based methods, as well as traditional partial typing methods, can produce very misleading conclusions. Overall, our findings demonstrate that nonclonal resistance gene dissemination can be extremely rapid, presenting significant challenges for public health surveillance and achieving effective control of antibiotic resistance.

Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study.

BACKGROUND: Slow and cumbersome laboratory diagnostics for Mycobacterium tuberculosis complex (MTBC) risk delayed treatment and poor patient outcomes. Whole-genome sequencing (WGS) could potentially provide a rapid and comprehensive diagnostic solution. In this prospective study, we compare real-time WGS with routine MTBC diagnostic workflows. METHODS: We compared sequencing mycobacteria from all newly positive liquid cultures with routine laboratory diagnostic workflows across eight laboratories in Europe and North America for diagnostic accuracy, processing times, and cost between Sept 6, 2013, and April 14, 2014. We sequenced specimens once using local Illumina MiSeq platforms and processed data centrally using a semi-automated bioinformatics pipeline. We identified species or complex using gene presence or absence, predicted drug susceptibilities from resistance-conferring mutations identified from reference-mapped MTBC genomes, and calculated genetic distance to previously sequenced UK MTBC isolates to detect outbreaks. WGS data processing and analysis was done by staff masked to routine reference laboratory and clinical results. We also did a microcosting analysis to assess the financial viability of WGS-based diagnostics. FINDINGS: Compared with routine results, WGS predicted species with 93% (95% CI 90-96; 322 of 345 specimens; 356 mycobacteria specimens submitted) accuracy and drug susceptibility also with 93% (91-95; 628 of 672 specimens; 168 MTBC specimens identified) accuracy, with one sequencing attempt. WGS linked 15 (16% [95% CI 10-26]) of 91 UK patients to an outbreak. WGS diagnosed a case of multidrug-resistant tuberculosis before routine diagnosis was completed and discovered a new multidrug-resistant tuberculosis cluster. Full WGS diagnostics could be generated in a median of 9 days (IQR 6-10), a median of 21 days (IQR 14-32) faster than final reference laboratory reports were produced (median of 31 days [IQR 21-44]), at a cost of £481 per culture-positive specimen, whereas routine diagnosis costs £518, equating to a WGS-based diagnosis cost that is 7% cheaper annually than are present diagnostic workflows. INTERPRETATION: We have shown that WGS has a scalable, rapid turnaround, and is a financially feasible method for full MTBC diagnostics. Continued improvements to mycobacterial processing, bioinformatics, and analysis will improve the accuracy, speed, and scope of WGS-based diagnosis. FUNDING: National Institute for Health Research, Department of Health, Wellcome Trust, British Colombia Centre for Disease Control Foundation for Population and Public Health, Department of Clinical Microbiology, Trinity College Dublin.

Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis.

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes.

Mycobacterial DNA extraction for whole-genome sequencing from early positive liquid (MGIT) cultures.

We developed a low-cost and reliable method of DNA extraction from as little as 1 ml of early positive mycobacterial growth indicator tube (MGIT) cultures that is suitable for whole-genome sequencing to identify mycobacterial species and predict antibiotic resistance in clinical samples. The DNA extraction method is based on ethanol precipitation supplemented by pretreatment steps with a MolYsis kit or saline wash for the removal of human DNA and a final DNA cleanup step with solid-phase reversible immobilization beads. The protocol yielded ≥0.2 ng/µl of DNA for 90% (MolYsis kit) and 83% (saline wash) of positive MGIT cultures. A total of 144 (94%) of the 154 samples sequenced on the MiSeq platform (Illumina) achieved the target of 1 million reads, with <5% of reads derived from human or nasopharyngeal flora for 88% and 91% of samples, respectively. A total of 59 (98%) of 60 samples that were identified by the national mycobacterial reference laboratory (NMRL) as Mycobacterium tuberculosis were successfully mapped to the H37Rv reference, with >90% coverage achieved. The DNA extraction protocol, therefore, will facilitate fast and accurate identification of mycobacterial species and resistance using a range of bioinformatics tools.

Temporal and spatial changes in the microbial bioaerosol communities in green-waste composting.

In this study, the microbial community within compost, emitted into the airstream, downwind and upwind from a composting facility was characterized and compared through phospholipid fatty acid analysis and 16S rRNA gene analysis using denaturing gradient gel electrophoresis and bar-coded pyrosequencing techniques. All methods used suggested that green-waste composting had a significant impact upon bioaerosol community composition. Daily variations of the on-site airborne community showed how specific site parameters such as compost process activity and meteorological conditions affect bioaerosol communities, although more data are required to qualify and quantify the causes for these variations. A notable feature was the dominance of Pseudomonas in downwind samples, suggesting that this genus can disperse downwind in elevated abundances. Thirty-nine phylotypes were homologous to plant or human phylotypes containing pathogens and were found within compost, on-site and downwind microbial communities. Although the significance of this finding in terms of potential health impact was beyond the scope of this study, it clearly illustrated the potential of molecular techniques to improve our understanding of the impact that green-waste composting emissions may have on the human health.

Evaluation of inflammatory effects of airborne endotoxin emitted from composting sources.

Because of the lack of effective methodology, the biological effects of environmental endotoxin have not been assessed. Here we have collected and measured airborne endotoxin at different locations around composting sites. Increased endotoxin concentrations were observed close to composting activities and also at nearby boundary areas. Analysis of proinflammatory effects of the environmental endotoxin on interleukin (IL)-8 and IL-6 release from human D562 pharyngeal epithelial and MM6 monocytic cell cultures showed an association between endotoxin level and cytokine induction. The cytokine-inducing effect of bioaerosol extracts was inhibited by polymyxin B, indicating that endotoxin was the cause of cytokine responses we found. The environmental endotoxin was also more active for stimulating cytokines in airway epithelial cells than commercially purified Escherichia coli endotoxin. Our results suggest that these in vitro inflammatory cell models may contribute to the assessment of health impacts of environmental endotoxin.